1. Field of the Invention
The present invention relates to a quantitative evaluation system for multiagent grouping and a method thereof. More particularly, the present invention relates to a quantitative evaluation system for multiagent grouping and a method thereof, which enables agents to be grouped in such a manner as to ensure efficient agent cooperation by quantitatively evaluating the characteristics of individual agents in a multiagent system.
2. Background Art
As generally known in the art, a software agent taking the place of human intelligent decision is introduced into a ubiquitous computing environment, and particularly how to efficiently group a plurality of agents is an important issue in a multiagent environment where a plurality of agents work together. That is, in a multiagent system, it is very important to organize an agent community appropriately, according to the object of the community to be grouped and agent characteristics. Therefore, in order to efficiently handle a specific task, it is essential to perceive agent characteristics and discover an agent optimally matched to the handling of the task. In a multiagent system where a plurality of agents work together, it is important to appropriately model the attributes of agents and group the agents based on the modeling so as to efficiently organize and manage the multiagent system. With regard to this, each agent serves as a producer or consumer of information.
Reference will now be made to agents with reference to FIG. 1, which illustrates conventional agents by way of example.
An agent refers to the subject producing or consuming at least one type of-information. The characteristic of an agent is defined based on information produced or consumed by the agent. The individuality of an agent is represented by the following criteria:                the type of information handled by an agent        whether an agent produces or consumes handling information        the amount of information handled by an agent        
As illustrated in FIG. 1, a temperature sensor agent cyclically produces information on sensed temperature as time goes by, and consumes sampling feedback information indicating at which time intervals the temperature sensor agent gathers temperature information. Further, a weather agent consumes a temperature information stream, a wind direction information stream and a humidity information stream produced by the temperature sensor agent, a wind direction sensor agent and a humidity sensor agent, respectively, and produces a weather information stream by processing them. The so-produced weather information is consumed by schedule agents and consumers in other communities. It can be intuitively understood that the temperature sensor agent is closely connected with the weather agent and thus they efficiently operate when grouped into one community.
An example of such multiagent technologies is disclosed in Korean Patent Application Laid-open No. 2000-0049800, published on Aug. 8, 2000 and entitled “System and Method for Optimal Brokerage and Automated Negotiation Based on Multiagent in Electronic Commerce”.
The technology disclosed in Korean Patent Application Laid-open No. 2000-0049800 relates to a multiagent-based system and a multiagent-based method for optimal brokerage and automated negotiation in electronic commerce, which creates virtual agents representing sellers, purchasers and brokers, respectively, intermediates between commerce parties coinciding in mutual demands via the created agents, and ultimately allows the agents acting on behalf of the commerce parties to make a contract in an ideal form through a negotiation process. This multiagent-based system includes a web server unit which a plurality of purchasers and a plurality of sellers access, an agent creating program for creating virtual agents representing purchasers and sellers who access the web server unit, a plurality of purchasing agents which are created by the agent creating program and represent the plurality of purchasers, respectively, a plurality of selling agents which are created by the agent creating program and represent the plurality of sellers, respectively, a brokerage agent for controlling the plurality of purchasing agents and the plurality of selling agents to be matched one-to-one to the most ideal counterparty by examining demands from the respective purchasing and selling agents, and a server control means for controlling the agent creating program to create agents of purchasers and sellers who access the web server unit and controlling the brokerage agent to allow each of the purchasing and selling agents to select the most ideal counterparty and negotiate with the selected counterparty. That is, the above-mentioned technology disclosed in Korean Patent Application No. 2000-0049800 improves the success rate of a contract by analyzing inclinations of purchasers and sellers based on artificial intelligence (AI) and connecting each of the purchasers and the sellers with the most appropriate counterparty, and provides the same effect as meeting between real persons by employing a scheme in which a purchasing agent and a selling agent perform negotiation while considering various situations based on learned information.
Another example of multiagent-related technologies is disclosed by C. H. Brooks, E. H. Durfee and A. Armstrong in “An Introduction to Congregation in Multiagent Systems”, Proceeedings of the Fourth International Conference on Multiagent Systems. 2000, pp. 79-86. The technology disclosed in this publication proposes a congregation model, which consists of plural agents having similar objects, in order to improve efficiency in a multiagent environment.
Yet another multiagent-related technology is disclosed by K. Naruse, M. Kinoshita and Y. Kakazu in “Group Formation of Agents with Two-dimensional Inner State and One-to-one Subjective Evaluation”, Proc. of IEEE Int. Symposium on Computational Intelligence in Robotics and Automation, Kobe, Japan, 2003, pp. 1492-1497. The technology disclosed in this publication proposes to form groups between agents based on individual satisfactions, and particularly to provide grouping based on the determination whether or not the grouping achieves satisfactions according to the roles of agents.
However, in conventional multiagent-related technologies including the technology disclosed in Korean Patent Application No. 2000-0049800, there is a problem in that the yield is reduced due to inundation with unnecessary information and the starvation of information desired by agents.
Further, in conventional multiagent grouping technologies, there is a problem in that an evaluation is made of agent characteristics based on only qualitative criteria.
Further, in the technology disclosed in the publication by C. H. Brooks, E. H. Durfee and A. Armstrong, the role of agents is established on the assumption of only one of the roles of a seller and a buyer, and thus there is a problem in that this technology is somewhat irrelevant to distributed ubiquitous computing in which the roles demanded of agents dynamically change.
Further, the technology disclosed in the publication by K. Naruse, M. Kinoshita and Y. Kakazu is insufficient for conducting efficient grouping because it is based on only individual satisfactions.